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Habit and Intention in Everyday Life: The Multiple Processes by Which Past Behavior Predicts Future Behavior


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Past behavior guides future responses through 2 processes. Well-practiced behaviors in constant contexts recur because the processing that initiates and controls their performance becomes automatic. Frequency of past behavior then reflects habit strength and has a direct effect on future performance. Alternately, when behaviors are not well learned or when they are performed in unstable or difficult contexts, conscious decision making is likely to be necessary to initiate and carry out the behavior. Under these conditions, past behavior (along with attitudes and subjective norms) may contribute to intentions, and behavior is guided by intentions. These relations between past behavior and future behavior are substantiated in a meta-analytic synthesis of prior research on behavior prediction and in a primary research investigation.
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... Traditionally, in habit research, context is seen as a trigger initiating a habit (Wood and Rünger, 2016). Ouellette and Wood (1998) showed in a meta-analysis that behavior that was previously performed in stable (vs. unstable) contexts was considerably less guided by intention. ...
... This instruction triggers planning of the study behavior that lies before them as conscious decisions on the time and place for each repetition need to be made before each execution, which could have created an intentional focus on the task at hand, potentially resulting in increased situational intention and deliberation concerning the target behavior. As Ouellette and Wood (1998) famously showed, intention is a stronger predictor for future behavior if the behavior was performed seldomly and in varying contexts in the past, which is, next to the frame of participating in an empirical study, a second possible factor that might have increased the habit repetition count in the variable context group. Thus, a milder manipulation of context stability, which would not trigger planning, intention, and deliberation, might result in less total habit repetitions. ...
... Thus, a habit with high execution automaticity should more easily be transferrable to different contexts because of a higher automaticity buffer, while fragile habits (e.g., newly developing and/or complex ones) would suffer much more even from slightly degraded context conditions by taxing already scarce executional automaticity, which would result, as we know, in higher motivational impairments during the habit performance (Stojanovic et al., 2020(Stojanovic et al., , 2021. As modern habit research evolves, the resolution of our understanding goes from rather coarse to more refined: From mere frequency to automaticity (Gardner, 2012) to differentiated instigation and execution automaticity (Gardner et al., 2016); and from mere stable contexts (e.g., Ouellette and Wood, 1998) to measured perceived context stability (this paper) to potentially differentiated trigger and execution effects of context in the future. However, context as a part of habit anatomy is currently still pixelated and more research is needed to empirically distinguish these two types of assumed context effects. ...
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In this paper, we investigate the effects of context stability on automaticity and goal attainment in intentional habit building. We used hierarchical growth curve modeling and multilevel mediation to test our hypotheses on two datasets. In Study 1, N = 95 university students ( N = 2,482 habit repetitions) built new study habits over a period of 6 weeks with manipulated context stability. One group was instructed to constantly vary the context of their habit repetitions by changing rooms and times and the other group was instructed to keep the context of habit performance stable. In Study 2, N = 308 habits ( N = 2,368 habit repetitions) from N = 218 users of a published habit building app were analyzed without manipulating but measuring context stability. We found the same pattern in both datasets: Context stability predicted more automaticity and higher habit repetition goal attainment. We also found that the effect of context stability on habit repetition goal attainment was partially mediated by automaticity in both datasets. These results show that context does not only act as a trigger for habit instigation but also has an ongoing effect on habit execution.
... When a behavior has been performed many times in the past, subsequent behavior increasingly becomes under the control of an automated cognitive process (Aarts, Verplanken and van Knippenberg, 1998). Consumers form favorable intentions about acts they have frequently performed in the past (Ouellette and Wood, 1998), such as repeated use of the product, making them increasingly dependent on the habit (Gefen, 2003) thereby enhancing their BI. ...
Traditionally software products have been classified as utilitarian or hedonic based on the value they provide to the users. In this cross-disciplinary study, we introduce another category of software products called social products i.e., those which provide symbolic value to its users. However, we also suggest these three types of software products are ideal types. In reality, most software products are likely hybrid. They provide differing magnitude of all three values: Utilitarian, Hedonic and Social. We use the different levels (high, medium, and low) of these three values to classify products as predominantly Utilitarian, predominantly Hedonic, predominantly Social and five types of Hybrids. This classification of products offers a fresh perspective into how users view different products in terms of the value they provide to them. The insights from the study can be used to assess software product positioning and to develop suitable product development strategies.
... One reason frequently identified in transportation research to explain why people often cannot change their travel patterns to more environmental friendly travels is that habitual behaviors are strong barriers to behavioral change (Itzchakov et al., 2018;Lanzini and Khan, 2017;Ouellette and Wood, 1998). ...
... As past behaviour is typically a strong predictor of future behaviour (Ouellette & Wood, 1998) and ...
Digital behaviour change interventions provide convenient and personalised health support for users, and the opportunity to record substantial amounts of data about users’ interactions with the intervention. If analysed systematically, these data are able to explain how the intervention was effective, for whom and in what context, leading to recommendations on how the intervention and future dissemination may be improved. However, the volume of data, their complexity and diversity can become a barrier. The aim of this thesis was to devise and apply a method to support analyses of large-scale usage data. The framework for Analysing and Measuring Usage and Engagement Data (AMUsED) was developed to support researchers in establishing clear rationales for collecting usage metrics and undertaking inferential analyses. The framework was applied to usage analyses of two interventions addressing antimicrobial resistance by lowering unnecessary medication prescriptions: Internet Dr encourages self-care for respiratory tract infections thereby reducing avoidable GP visits; PRIMIT/Germ Defence intervention lowers transmission of viruses by increasing handwashing in the home. The process evaluations identified: what type of engagement was successful; specific improvements for the interventions; and the importance of context for using the intervention. Internet Dr findings revealed that the intervention is effective at raising enablement to self-care for users who are not experiencing symptoms, suggesting the structure and theory-based content are relevant for increasing self-care for other minor ailments. The PRIMIT/Germ Defence findings provide insight for public health campaigns by evidencing the value of targeting multiple handwashing situations where risk of transmission is high. A scoping review was carried out to capture how ‘usage’ and ‘engagement’ with digital interventions are conceptualised. The review confirms the need for a practical and generalisable method for usage analyses, and the AMUsED framework is the only method proposed to do this. The process evaluations structured by the framework demonstrate how it supports researchers in conducting analyses of large-scale data, leading to a better understanding of digital intervention engagement, specific recommendations for improvement, and informs our understanding of applying behaviour change theories to a target health issue. These types of findings will lead to more effective digital behaviour change interventions that provide better support for the people who use them.
... Some behaviour can be predicted from actions in the past (Aarts, et al., 1998) and some processes can determine which past behaviours can better predict the future (Ouellette & Wood, 1998). Travel behaviour is related to social psychology (Anable, 2005; Van et al., 2010), and such behaviour may be influenced by the interplay of infrastructure, neighbourhood characteristics and social circumstances and aims to understand the influence of a variety of Psychological/Economical, Social/Cultural, Environmental/Physical and Structural/Managerial factors (Guell et al., 2012). ...
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CORONAVIRUS (COVID-19) as a global outbreak crisis can be considered as an opportunity to reflect on the current tourism industry policies to transform tourism and hospitality industry (Hall et al., 2020) to make them consistent with sustainable development goals and research in tourism development (Gössling et al., 2020). One possible area of immediate attention may be destination sustainability framework (DSF) which assess destination vulnerability (Calgaro et al., 2014) and resilience as a complex adaptive system (Lew, 2014). International tourism and its global public health consequences (Richter, 2003), and tourism recovery strategy (Yeh, 2020) as well as best practice (Page et al., 2006) against the pandemic, need to be considered. Severe Acute Respiratory Syndrome (SARS) outbreak in 2003 which started in southern China and adversely effected Asian tourism for a while, (McKercher & Chon, 2004). This crisis showed that integrated national and international tourism crisis recovery strategies are needed, and also it emphasized the need for stronger international participation among tourism stakeholders to develop efficient responses to cross�border crises. In an article by Page, 2006 on Scotland’s influenza pandemic, he suggests that for events such as a pandemic to be understood, we need to build multidisciplinary research teams (economist, a scenario planner, tourism researchers, doctors, civil servants from the public health field and collaboration with a number of major industry leaders and influential organizations dealing with mass tourism) who can communicate and study the issue, focused on a common goal and crisis management can be harnessed towards a common purpose.
... As prior research continually demonstrates, attitudes predict behaviors (Newstrom & Davis, 1993) and past behaviors generally predict future behaviors (Oullette & Wood, 1998). ...
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Despite the longstanding issues within the correctional officer occupation (e.g., high turnover, absenteeism), decades of research have tended to focus solely on the negative consequences of correctional officer work, rather than on the unique personal characteristics of the officers themselves. This omission is surprising as it is highly probable that each person experiences correctional work differently, with variation potentially hinging on the unique views and characteristics individuals bring with them to the job. Just as the "importation model" of prison adaptation recognizes the importance of pre-prison characteristics in explaining offender behavior, we argue that the unique personal experiences and social histories correctional officers import with them might shape the way they react to prison work. Thus, by thematically, descriptively, and multivariately examining three theoretically germane pre-prison work characteristics of 673 pre-service correctional officers (career motivations, attitudes toward prisoners, occupational histories), this call for research aims to raise awareness of the less studied factors within the correctional officer literature. Understanding the backgrounds and attitudes of newly hired correctional officers may potentially assist in the recruitment and retainment of these crucial employees in the prison system both in the United States and abroad.
Coal mine accidents seriously affect people’s safety and social development, and intelligent mines have improved the production safety environment. However, safety management and miners’ work in intelligent mines face new changes and higher requirements, and the safety situation remains challenging. Therefore, exploring the key influencing factors of miners’ unsafe behaviors in intelligent mines is important. Our work focuses on (1) investigating the relationship and hierarchy of 20 factors, (2) using fuzzy theory to improve the decision-making trial and evaluation laboratory (DEMATEL) method and introducing the maximum mean de-entropy (MMDE) method to determine the unique threshold scientifically, and (3) developing a novel multi-criteria decision-making (MCDM) model to provide theoretical basis and methods for managers. The main conclusions are as follows: (1) the influence degree of government regulation, leadership attention, safety input level, safety system standardization, and dynamic supervision intensity exert the most significant influence on the others; (2) the causality of government regulation, which is the deep factor, is the highest, and self-efficacy displays the smallest causality, and it is the most sensitive compared to various other factors; (3) knowledge accumulation ability, man–machine compatibility, emergency management capability, and organizational safety culture has the highest centrality among the individual factors, device factors, management factors, and environmental factors, respectively. Thus, corresponding management measures are proposed to improve coal mine safety and miners’ occupational health.
Much of the research on digital wellbeing (DWB) in HCI focuses on increasing happiness, reducing distraction, or achieving goals. Distinct from this is a conceptualization of DWB sensitive to another commonly observed type of interaction with technology: the interstitial, the mundane, or the “meaningless.” We examine DWB with a mixed methods approach – a series of three separate but related Experience Sampling Method studies (ESM) paired with user interviews and diary studies. Through both quantitative and interpretive analyses, we clarify the distinction between what is identifiable – in terms of what is observable, measurable, or significant – and what is, from a human perspective, important. Extending from our analysis, we define and operationalize meaningless interactions with technology, highlighting how those interactions can contribute to self-empathy and contentment. Ultimately, we suggest a framing for DWB sensitive to these observations to support design for people in their lived experiences.
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Two meta-analyses were conducted to Investigate the effectiveness of the Fishbein and Ajzen model in research to date. Strong overall evidence for the predictive utility of the model was found. Although numerous instances were identified in which researchers overstepped the boundary conditions initially proposed for the model, the predictive utility remained strong across conditions. However, three variables were proposed and found to moderate the effectiveness of the model. Suggested extensions to the model are discussed and general directions for future research are given.